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Amazon AIF-C01 Exam Syllabus Topics:
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Amazon AWS Certified AI Practitioner Sample Questions (Q102-Q107):
NEW QUESTION # 102
A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock.
What are the key benefits of using Amazon Bedrock agents that could help this retailer?
Answer: C
Explanation:
Amazon Bedrock Agents provide the capability to automate repetitive tasks and orchestrate complex workflows using generative AI models. This is particularly beneficial for customer support inquiries, where quick and efficient processing is crucial.
Option B (Correct): "Automation of repetitive tasks and orchestration of complex workflows": This is the correct answer because Bedrock Agents can automate common customer service tasks and streamline complex processes, improving response times and efficiency.
Option A: "Generation of custom foundation models (FMs) to predict customer needs" is incorrect as Bedrock agents do not create custom models.
Option C: "Automatically calling multiple foundation models (FMs) and consolidating the results" is incorrect because Bedrock agents focus on task automation rather than combining model outputs.
Option D: "Selecting the foundation model (FM) based on predefined criteria and metrics" is incorrect as Bedrock agents are not designed for selecting models.
AWS AI Practitioner Reference:
Amazon Bedrock Documentation: AWS explains that Bedrock Agents automate tasks and manage complex workflows, making them ideal for customer support automation.
NEW QUESTION # 103
A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide.
The employees have minimal experience with technology.
Which solution meets these requirements?
Answer: C
Explanation:
Generative Pre-trained Transformers (GPT) are suitable for building an AI-based application that can generate SQL queries from natural language input provided by employees.
* GPT for Natural Language Processing:
* GPT models are designed for understanding and generating human-like text based on natural language input.
* They can be fine-tuned to interpret specific tasks, such as converting natural language queries into SQL queries.
* Why Option A is Correct:
* Natural Language Understanding: GPT is highly effective for tasks that require understanding of human language and generating structured outputs like SQL.
* User-Friendly: Requires minimal technology experience from employees, as they provide simple text input.
* Why Other Options are Incorrect:
* B. Residual neural network: Typically used in computer vision tasks, not for natural language- to-SQL conversion.
* C. Support vector machine: Used for classification tasks, not for generating structured queries from text.
* D. WaveNet: A deep generative model for audio data, unrelated to text-to-SQL tasks.
NEW QUESTION # 104
A medical company wants to develop an AI application that can access structured patient records, extract relevant information, and generate concise summaries.
Which solution will meet these requirements?
Answer: C
NEW QUESTION # 105
Which component of Amazon Bedrock Studio can help secure the content that AI systems generate?
Answer: B
NEW QUESTION # 106
A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock.
What are the key benefits of using Amazon Bedrock agents that could help this retailer?
Answer: C
Explanation:
Amazon Bedrock Agents provide the capability to automate repetitive tasks and orchestrate complex workflows using generative AI models. This is particularly beneficial for customer support inquiries, where quick and efficient processing is crucial.
Option B (Correct): "Automation of repetitive tasks and orchestration of complex workflows": This is the correct answer because Bedrock Agents can automate common customer service tasks and streamline complex processes, improving response times and efficiency.
Option A: "Generation of custom foundation models (FMs) to predict customer needs" is incorrect as Bedrock agents do not create custom models.
Option C: "Automatically calling multiple foundation models (FMs) and consolidating the results" is incorrect because Bedrock agents focus on task automation rather than combining model outputs.
Option D: "Selecting the foundation model (FM) based on predefined criteria and metrics" is incorrect as Bedrock agents are not designed for selecting models.
AWS AI Practitioner References:
Amazon Bedrock Documentation: AWS explains that Bedrock Agents automate tasks and manage complex workflows, making them ideal for customer support automation.
NEW QUESTION # 107
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